Signals and Frequencies

From the Internet of Things (IoT), where we are today, we are just beginning to enter a new realm: the Internet of Everything (IoE), where things will gain context awareness, increased processing power, and greater sensing abilities. Add people and information into the mix and you get a network of networks where billions or even trillions of connections create unprecedented opportunities and give things that were silent a voice.

Cisco defines IoE as bringing together people, process, data, and things to make networked connections more relevant and valuable than ever before—turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries. (On Cisco POV, see also the video at the end of this post).

As more things, people, and data become connected, the power of the Internet (essentially a network of networks) grows exponentially. (See Metcalfe’s Law and Network effect).

A full realization of IoE will require some key enabling factors. In my opinion, the most crucial ones will be IPv6 implementation and, above all, a brand new software engineering approach. The manner in which software is developed hasn’t fundamentally changed since the 1960s. The orchestration of a paradigm shift is essential if the software industry is to ever become at least as innovative and productive as the hardware industry, which is following Moore’s Law. A new software science approach needs to be established to meet the requirements for the emerging IoE of unattended devices.

More on this subject:
What is the ‘Internet of everything’? – Answered by Peter H. Diamandis
Gartner Symposium: CIOs, Get ready for the IoE

HFT - Robot Wars

Robot Wars

This animated GIF created by the Nanex pictures the rise of high-frequency trading (or HFT) volumes across all US stock exchanges between 2007 and 2012. The initial murmur, the brewing storm, the final detonation: not just unsettling, it’s terrifying.

HFT trading volumes across all U.S. stock exchanges between 2007 and 2012
credit: Nanex Research, hosted by

This is what high frequency trading looks like, when specially programmed computers make massive bets at lightning speed.

We don’t know is what the long term consequences are of all this hyper-volume as depicted by the Nanex GIF and the kind of systemic risks created from the market’s ongoing evolution from human traders to rapidfire AI. Sometimes things go wrong, a software glitch, an algorithm gone rogue and the music stops, like a couple weeks ago when Knight Capital lost $10 million a minute when it’s trading platform went haywire or during the infamous Flash Crash when the Dow dropped 1000 points in mere minutes.

Read the excellent full Mother Board article here.